Analysis and Design of Primal-Dual Assignment Networks  

Oleh:

Jun, Wang ; Xia, Youshen

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 1 (1998), page 183-194.
Topik: networks; analysis; design; primal - dual assignment; networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The assignment problem is an archetypical combinatorial optimization problem having widespread applications. This paper presents two recurrent neural networks, a continuous - time one and a discrete - time one, for solving the assignment problem. Because the proposed recurrent neural networks solve the primal and dual assignment problems simultaneously, they are called primal - dual assignment networks. The primal - dual assignment networks are guaranteed to make optimal assignment regardless of initial conditions. Unlike the primal or dual assignment network, there is no time - varying design parameter in the primal - dual assignment networks. Therefore, they are more suitable for hardware implementation. The performance and operating characteristics of the primal - dual assignment networks are demonstrated by means of illustrative examples.

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